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Mendeley readers
Attention Score in Context
| Title |
Establishing an adjusted p-value threshold to control the family-wide type 1 error in genome wide association studies
|
|---|---|
| Published in |
BMC Genomics, October 2008
|
| DOI | 10.1186/1471-2164-9-516 |
| Pubmed ID | |
| Authors |
Priya Duggal, Elizabeth M Gillanders, Taura N Holmes, Joan E Bailey-Wilson |
| Abstract |
By assaying hundreds of thousands of single nucleotide polymorphisms, genome wide association studies (GWAS) allow for a powerful, unbiased review of the entire genome to localize common genetic variants that influence health and disease. Although it is widely recognized that some correction for multiple testing is necessary, in order to control the family-wide Type 1 Error in genetic association studies, it is not clear which method to utilize. One simple approach is to perform a Bonferroni correction using all n single nucleotide polymorphisms (SNPs) across the genome; however this approach is highly conservative and would "overcorrect" for SNPs that are not truly independent. Many SNPs fall within regions of strong linkage disequilibrium (LD) ("blocks") and should not be considered "independent". We proposed to approximate the number of "independent" SNPs by counting 1 SNP per LD block, plus all SNPs outside of blocks (interblock SNPs). We examined the effective number of independent SNPs for Genome Wide Association Study (GWAS) panels. In the CEPH Utah (CEU) population, by considering the interdependence of SNPs, we could reduce the total number of effective tests within the Affymetrix and Illumina SNP panels from 500,000 and 317,000 to 67,000 and 82,000 "independent" SNPs, respectively. For the Affymetrix 500 K and Illumina 317 K GWAS SNP panels we recommend using 10(-5), 10(-7) and 10(-8) and for the Phase II HapMap CEPH Utah and Yoruba populations we recommend using 10(-6), 10(-7) and 10(-9) as "suggestive", "significant" and "highly significant" p-value thresholds to properly control the family-wide Type 1 error. By approximating the effective number of independent SNPs across the genome we are able to 'correct' for a more accurate number of tests and therefore develop 'LD adjusted' Bonferroni corrected p-value thresholds that account for the interdepdendence of SNPs on well-utilized commercially available SNP "chips". These thresholds will serve as guides to researchers trying to decide which regions of the genome should be studied further. |
Mendeley readers
The data shown below were compiled from readership statistics for 173 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 2 | 1% |
| United States | 2 | 1% |
| Mexico | 2 | 1% |
| Hong Kong | 1 | <1% |
| Germany | 1 | <1% |
| Switzerland | 1 | <1% |
| Netherlands | 1 | <1% |
| Unknown | 163 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 40 | 23% |
| Student > Ph. D. Student | 32 | 18% |
| Student > Master | 21 | 12% |
| Student > Bachelor | 14 | 8% |
| Professor | 9 | 5% |
| Other | 33 | 19% |
| Unknown | 24 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 87 | 50% |
| Biochemistry, Genetics and Molecular Biology | 24 | 14% |
| Medicine and Dentistry | 9 | 5% |
| Psychology | 5 | 3% |
| Mathematics | 5 | 3% |
| Other | 19 | 11% |
| Unknown | 24 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 July 2014.
All research outputs
#14,600,874
of 25,374,917 outputs
Outputs from BMC Genomics
#4,932
of 11,244 outputs
Outputs of similar age
#86,679
of 104,769 outputs
Outputs of similar age from BMC Genomics
#58
of 68 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one has gotten more attention than average, scoring higher than 54% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 104,769 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 68 others from the same source and published within six weeks on either side of this one. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.